Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Antoine, Soloy"'
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 2, p 327 (2024)
This study delves into the morphodynamic changes of pebble beaches in response to storm events, employing a combination of observational and numerical approaches. This research focuses on three extreme events, meticulously examining morhological chan
Externí odkaz:
https://doaj.org/article/80297e66ac1c4b8bb3e9b0faca45d31a
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3659 (2020)
This article proposes a new methodological approach to measure and map the size of coarse clasts on a land surface from photographs. This method is based on the use of the Mask Regional Convolutional Neural Network (R-CNN) deep learning algorithm, wh
Externí odkaz:
https://doaj.org/article/c30f83bfe738410586082fca70b7bedb
While recent studies highlighted the great mobility of boulder beaches related to the impact of storm waves, numerous researches are still needed to better understand the morphodynamic of coastal boulder accumulations. This paper provides original da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f5de75ae56cbbe41c1469e5acc0bdf0
https://doi.org/10.5194/icg2022-359
https://doi.org/10.5194/icg2022-359
Autor:
Carlos López Solano, Emma Imen Turki, Yasser Hamdi, Antoine Soloy, Stéphane Costa, Benoit Laignel, Ángel David Gutiérrez Barceló, Nizar Abcha, Delphine Jacono, Robert Lafite
Publikováno v:
Water, Vol 14, Iss 321, p 321 (2022)
Water; Volume 14; Issue 3; Pages: 321
Water; Volume 14; Issue 3; Pages: 321
This research was carried out in the framework of the Surface Water and Ocean Topography (SWOT) program of the French National Centre of Space Studies (CNES). In the context of global climate change, increases in frequency and intensity of extreme ev
Autor:
Antoine, Soloy, Edoardo, Grottoli, Mark, Lorang, Bob de Graffenried, Ivan, Pascal, Bertoni, Duccio, Imen, Turki, Nicolas, Lecoq, Derek, Jackson, Emilia Guisado Pintado, Christophe, Ancey, Arthur, Trembanis, Benoit, Laignel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3728::7f393e87fd1f9fb545ade9445cadecb9
http://hdl.handle.net/11568/1122047
http://hdl.handle.net/11568/1122047
Publikováno v:
Marine Geology. 447:106796
Publikováno v:
Estuarine, Coastal and Shelf Science. 265:107694
Publikováno v:
Remote Sensing; Volume 12; Issue 21; Pages: 3659
Remote Sensing
Remote Sensing, MDPI, 2020, 12 (21), pp.3659. ⟨10.3390/rs12213659⟩
Remote Sensing, MDPI, 2020, 12, ⟨10.3390/rs12213659⟩
Remote Sensing, Vol 12, Iss 3659, p 3659 (2020)
Remote Sensing
Remote Sensing, MDPI, 2020, 12 (21), pp.3659. ⟨10.3390/rs12213659⟩
Remote Sensing, MDPI, 2020, 12, ⟨10.3390/rs12213659⟩
Remote Sensing, Vol 12, Iss 3659, p 3659 (2020)
This article proposes a new methodological approach to measure and map the size of coarse clasts on a land surface from photographs. This method is based on the use of the Mask Regional Convolutional Neural Network (R-CNN) deep learning algorithm, wh